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Emergence and suppression of cooperation by action visibility in transparent games.
- Source :
- PLoS Computational Biology, Vol 16, Iss 1, p e1007588 (2020)
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
Abstract
- Real-world agents, humans as well as animals, observe each other during interactions and choose their own actions taking the partners' ongoing behaviour into account. Yet, classical game theory assumes that players act either strictly sequentially or strictly simultaneously without knowing each other's current choices. To account for action visibility and provide a more realistic model of interactions under time constraints, we introduce a new game-theoretic setting called transparent games, where each player has a certain probability of observing the partner's choice before deciding on its own action. By means of evolutionary simulations, we demonstrate that even a small probability of seeing the partner's choice before one's own decision substantially changes the evolutionary successful strategies. Action visibility enhances cooperation in an iterated coordination game, but reduces cooperation in a more competitive iterated Prisoner's Dilemma. In both games, "Win-stay, lose-shift" and "Tit-for-tat" strategies are predominant for moderate transparency, while a "Leader-Follower" strategy emerges for high transparency. Our results have implications for studies of human and animal social behaviour, especially for the analysis of dyadic and group interactions.
- Subjects :
- Biology (General)
QH301-705.5
Subjects
Details
- Language :
- English
- ISSN :
- 1553734X and 15537358
- Volume :
- 16
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.687dd71afa784d2db897a4c4d6284c6b
- Document Type :
- article
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1007588